Understanding the characteristics of truck-involved crashes is of keen interest because such crashes are highly associated with greater potential leading to severer injury. The purpose of this study is to identify factors affecting injury severity of truck-involved crashes on freeways. In addition, a binary logistic regression technique is applied to identify causal factors affecting truck crash severity under normal and adverse weather conditions. Major findings from the analyses are discussed with truck operations strategies including speed enforcement, variable speed limit, and truck lane restriction, from the safety enhancement point of view. The results of this study would be useful for developing traffic control and operations strategies to reduce truck-involved crashes and injury severity in practice.

This study proposes a novel performance measure, which is referred to as Hazardous Spacing Index (HSI), to be used for evaluating safety of traffic stream on freeways. The basic principle of the proposed methodology is to investigate whether drivers would have sufficient stopping sight distance (SSD) under limited visibility conditions to eliminate rear-end crash potentials at every time step. Both Road Weather Information Systems (RWIS) and Vehicle Detection Systems (VDS) data were used to derive visibility distance (VD) and SSD, respectively. Moreover, the K-Nearest Neighbors (KNN) method was adopted to predict both VD and SSD in estimating predictive HSIs, which would be used to trigger advanced warning information to encourage safer driving. The outcome of this study is also expected to be used for monitoring freeway traffic stream in terms of safety. 본 연구는 도로 기상정보 시스템(RWIS

: In this study, for the purpose of reduction of CO2 gas emission and to increase recovery of waste heat from ships, the ORC(Organic Rankine Cycle) is investigated and offered for the conversion of temperature heat to electricity from waste heat energy from ships. Simulation is performed with waste heat from the exhaust gasse which is relatively high temperature and cooling sea water which is relatively low temperature from ships. The result shows that 1,000㎾ power generation is available from exhaust gas and 600㎾power generation is available from sea water cooling system. Different fluid is used for simulation of the ORC system with variable temperature and flow condition and efficiency of system and output power is compared.

Recently, commercialization of autonomous vehicles has been emerged as one of the important issues. Especially, it is needed to operate roadways safely in the mixed traffic condition with autonomous and non-autonomous vehicles. For this reason, implementation of managed lane specifically for autonomous vehicles has been widely suggested to minimize the friction between the autonomous vehicle and the non-autonomous driving vehicle. In this study, we analyzed the impact of implementing autonomous bus managed lane on expressway according to the market penetration rate, traffic volume (level of service), and length of influence area using microscopic traffic simulation. Particularly, the minimum weaving section length has been calculated based on different road environments. As a result, the minimum weaving section for the autonomous bus to enter the managed lane was 600-1200m. In addition, the results also indicated that weaving section length from 800-1200m was found to be the suggested entry weaving section length. It is expected that the results of this study can provide insights for designing and operating managed lane for autonomous vehicles in the future.

The aging problem is a significant issue in terms of overall aspects of society, and the need for making traffic safety policies is of keen interest because the increase in elderly drivers may have an impact on traffic safety. Therefore, the primary purpose of this study was to identify the characteristics of elderly drivers' driving behaviors on freeways and to evaluate the workload of elderly drivers. The driving behavior of subjects was evaluated by utilizing the trajectory data optained from driving simulation experiments. In addition, the workload of subjects was estimated based on the ratio of beta waves to entire brain waves, which were collected while the participants were conducting the driving experiment. As a result, the average of elderly drivers' speed was lower by 6% than non-elderly drivers. However, the average of the standard deviation of elderly drivers' speed, which is a measure of effectiveness to represent the longitudinal driving stability, was higher about 25% than non-elderly drivers. Moreover, the average of the standard deviation of the lane position of elderly drivers on freeways, which indicates how they are stable on lateral driving, was higher about 31% compared to non-elderly drivers. Besides, the amount of beta wave of elderly drivers, which shows a driver's psychological workload, was higher about 11% than non-elderly drivers. This study is expected to be utilized as a fundamental data when policies for elderly drivers are established in order to improve traffic safety in the aging society.